An explanation of the General Observation Classes and "Special Purpose domains" might be in order. Maybe the concept map from the SDTM model (PDF page 8) or a modified version of it would be sufficient at this stage of the TIG.
In draft
Standards in this guide are end-to-end implementations of CDISC models designed to ensure the traceability and transparency of data across activities in the data lifecycle. Implementation of models per this guide in relation to activities which support collection, tabulation, analysisThe TIG provides instructions and recommendations to implement these models for the collection, representation, and exchange of tobacco product data are further described in the table below.
Observations
are imputed for analysis purposes, the imputed dates will be generated in the Analysis Data Model (ADaM) but not in the SDTM submission data sets.
. Controlled terminology and formats support implementation of all models. Standards for data exchange are applicable to all use cases and allow for the exchange of metadata for CRFs, tabulation datasets, and analysis datasets.
The following table describes implementation of CDISC models with supporting standards and TIG sections.
| Metadataspec |
|---|
| Metadataspec |
|---|
Standards for Collection | Standards for Tabulation | Standards for Analysis | CDISC CDASH Model - In this guide, the CDASH Model is implemented to support development of CRFs for the Product Impact on Individual Health use case only. The CDASH Model is the earliest model implemented for this use case.
- The CDASH Model defines a basic set of data collection fields that are expected to be present on the majority of CRFs.
- The use of CDASH data collection fields and variables facilitates mapping to tabulation datasets implemented from the SDTM.
- When data can be collected as it will be represented in a tabulation dataset, with no transformations or derivations, the TIG SDTM variable names are presented in the TIG CDASH to collect the data.
- In cases where collected data must be transformed or reformatted prior to inclusion in a tabulation dataset, or where a corresponding SDTMIG variable does not exist, CDASH has created standardized data collection variable names.
| CDISC SDTM
- The SDTM is implemented for use cases
CDISC ADaM | Standards for Data Exchange | | Metadataspec |
|---|
| Standards for Collection | Standards for Tabulation | Standards for Analysis | CDISC CDASH Model - In this guide, the CDASH Model is implemented to support development of CRFs for the Product Impact on Individual Health use case only. The CDASH Model is the earliest model implemented for this use case.
- The CDASH Model defines a basic set of data collection fields that are expected to be present on the majority of CRFs.
- The use of CDASH data collection fields and variables facilitates mapping to tabulation datasets implemented from the SDTM.
- When data can be collected as it will be represented in a tabulation dataset, with no transformations or derivations, the TIG SDTM variable names are presented in the TIG CDASH to collect the data.
- In cases where collected data must be transformed or reformatted prior to inclusion in a tabulation dataset, or where a corresponding SDTMIG variable does not exist, CDASH has created standardized data collection variable names.
| CDISC SDTM - The SDTM is implemented for use cases
CDISC ADaM - The ADaM is described for general usage as well as being implemented for use cases
- Several of the use cases describe dataset classes not yet defined in the ADaM
| | Use Case | Standards for Data Collection | Standards for Data Tabulation | Standards for Data Analysis | Product description | Not applicable, as data are not collected via CRFs. | Data: Controlled terminology and formats: Data exchange: | Data: Controlled terminology and formats: Data exchange: | Nonclinical | Not applicable, as data are not collected via CRFs. | Data: Controlled terminology and formats: Data exchange: | Not applicable, as data may be analyzed directly from tabulation datasets. | Product impact on individual health | Data: Controlled terminology and formats: Data exchange: | Data: Controlled terminology and formats: Data exchange: | Data: Controlled terminology and formats: Data exchange: | Product impact on population health | Not applicable, as data input parameters generated for population modeling are calculated via upstream analyses. | Not applicable, as data input parameters generated for population modeling are calculated via upstream analyses. | Data: Controlled terminology and formats: Data exchange: | |